Various embodiments of the present technology may provide methods and system for a battery. The system may provide a fuel gauge circuit configured to select an energy curve from a plurality of energy curves and determine a remaining energy value based on the selected energy curve and a computed remaining capacity of the battery. The fuel gauge circuit controls a current to a load based on the remaining energy value.
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1. An apparatus for monitoring a battery, comprising: a voltage sensor configured to measure a voltage of the battery; a calculation circuit configured to measure a remaining capacity of the battery according to the measured voltage; a memory configured to store: a predetermined voltage threshold; and predetermined battery data comprising a plurality of energy curves; and a logic circuit configured to: determine if the measured voltage of the battery is less than the predetermined voltage threshold; select one energy curve from the plurality of energy curves based on the measured voltage of the battery when the measured voltage is determined to be less than the predetermined voltage; and select a remaining energy value from the selected energy curve based on the measured remaining capacity.
The apparatus monitors a battery's state of charge to estimate its remaining energy. It addresses the challenge of accurately determining battery capacity as voltage decreases, particularly in low-voltage conditions where traditional methods may fail. The system includes a voltage sensor that measures the battery's voltage and a calculation circuit that determines the remaining capacity based on this measurement. A memory stores a voltage threshold and battery data, including multiple energy curves that represent the battery's energy characteristics at different voltage levels. A logic circuit compares the measured voltage against the threshold. If the voltage is below the threshold, the circuit selects an appropriate energy curve from the stored data based on the current voltage. It then uses the measured remaining capacity to select a corresponding remaining energy value from the chosen curve. This approach improves energy estimation accuracy by dynamically adjusting the reference curve based on the battery's voltage state, ensuring reliable performance even at low voltages. The system is particularly useful for applications requiring precise battery monitoring, such as electric vehicles or portable devices.
2. The apparatus according to claim 1 , further comprising a timer configured to count to a predetermined time.
A system for managing operations in a technical process includes a control unit that monitors and regulates the process based on predefined parameters. The control unit detects deviations from these parameters and triggers corrective actions to maintain optimal performance. The system further includes a timer that counts to a predetermined time, allowing for time-based control or synchronization of operations. The timer can be used to enforce time limits, schedule events, or coordinate actions within the system. The control unit and timer work together to ensure the process operates efficiently and within specified constraints, improving reliability and performance. This system is applicable in industrial automation, manufacturing, or any process requiring precise control and timing.
3. The apparatus according to claim 2 , wherein the logic circuit is further configured to reset the timer and restart the timer to count an elapsed time if the measured battery voltage is less than the predetermined threshold.
A battery monitoring system detects and responds to low battery voltage conditions in electronic devices. The system includes a voltage measurement circuit that continuously monitors the battery voltage and compares it to a predetermined threshold. If the voltage falls below this threshold, a logic circuit triggers a reset and restart of a timer that tracks elapsed time. This ensures accurate timekeeping even when the battery voltage fluctuates, preventing premature device shutdown or data loss. The system may also include a power management unit that adjusts power distribution to critical components when low voltage is detected, extending operational time. The logic circuit may further implement additional safeguards, such as disabling non-essential functions or activating a low-power mode, to conserve energy. The timer reset mechanism ensures that time-sensitive operations remain reliable, even under varying battery conditions. This approach is particularly useful in portable devices where battery life and performance stability are critical. The system may also log voltage events for diagnostic purposes, allowing for predictive maintenance or battery health monitoring. By dynamically responding to voltage fluctuations, the apparatus enhances device reliability and user experience.
4. The apparatus according to claim 2 , wherein the battery recovers to an initial voltage after the predetermined time has elapsed.
This invention relates to an apparatus for managing battery recovery in electronic devices. The problem addressed is ensuring reliable battery performance by allowing the battery to recover to its initial voltage after a predetermined time has elapsed, particularly in systems where the battery is subjected to high discharge rates or intermittent usage. The apparatus includes a battery, a voltage monitoring circuit, and a control unit. The voltage monitoring circuit continuously measures the battery's voltage and detects when it drops below a threshold level. The control unit then activates a recovery mode, where the battery is temporarily disconnected from the load or its discharge rate is reduced. After a predetermined time, the control unit re-enables full operation, allowing the battery to recover to its initial voltage. This ensures consistent power delivery and extends battery lifespan by preventing deep discharge cycles. The apparatus may also include a timer to track the elapsed time and a comparator to verify voltage recovery. The invention is particularly useful in portable devices, medical equipment, and industrial systems where stable power supply is critical. The recovery mechanism helps maintain optimal battery health and performance over extended periods.
5. The apparatus according to claim 1 , wherein each energy curve from the plurality of energy curves comprises remaining energy values and corresponding remaining capacity values.
This invention relates to an apparatus for managing energy storage systems, particularly focusing on tracking and analyzing energy curves to optimize performance. The apparatus addresses the challenge of accurately monitoring the state of charge and health of energy storage devices, such as batteries, by generating and analyzing energy curves that represent the relationship between remaining energy and remaining capacity. The apparatus includes a processing unit that generates a plurality of energy curves, each representing the energy storage device's performance under different conditions. Each energy curve consists of remaining energy values and corresponding remaining capacity values, allowing for precise tracking of the device's state. The processing unit further analyzes these curves to determine key metrics such as state of charge, state of health, and efficiency, enabling real-time adjustments to improve energy management. By comparing multiple energy curves, the apparatus can identify degradation patterns, predict future performance, and optimize charging/discharging cycles. This ensures prolonged battery life and enhanced efficiency in energy storage applications. The system may also integrate with external data sources to refine predictions and adapt to varying operational conditions. The invention is particularly useful in electric vehicles, renewable energy storage, and grid stabilization systems where accurate energy monitoring is critical.
6. The apparatus according to claim 1 , wherein the memory is further configured to store previously-measured voltage data.
A system for monitoring and analyzing electrical voltage measurements includes a memory configured to store previously-measured voltage data alongside current voltage measurements. The system also includes a processor that processes the stored voltage data to detect anomalies, trends, or deviations from expected voltage levels. The processor may compare current measurements against historical data to identify patterns, predict potential failures, or optimize power distribution. The memory stores both real-time and historical voltage readings, enabling long-term analysis and predictive maintenance. The system may be integrated into power grids, industrial machinery, or electronic devices to ensure stable and efficient voltage regulation. By analyzing stored voltage data, the system can improve reliability, reduce downtime, and enhance energy efficiency in electrical systems. The apparatus may also include communication interfaces to transmit voltage data to external monitoring systems or control units for further analysis or automated adjustments. The stored voltage data allows for retrospective analysis, helping to diagnose issues that may not be immediately apparent during real-time monitoring.
7. The apparatus according to claim 6 , wherein the logic circuit is further configured to estimate a lifespan of the battery based on the previously-measured voltage data and the selected energy curve.
A battery monitoring apparatus includes a logic circuit that analyzes voltage data from a battery and selects an energy curve to estimate the battery's state of charge (SOC). The logic circuit further estimates the battery's lifespan by comparing the previously-measured voltage data with the selected energy curve. The apparatus may also include a voltage sensor to measure the battery's voltage and a communication interface to transmit the SOC and lifespan data to an external device. The energy curve selection is based on factors such as battery type, temperature, and usage patterns. The lifespan estimation helps predict when the battery may need replacement, improving maintenance planning and reducing downtime. The apparatus is designed for use in electric vehicles, renewable energy storage systems, or portable electronic devices where accurate battery monitoring is critical. The system ensures reliable performance by continuously updating the SOC and lifespan estimates based on real-time voltage measurements and historical data.
8. The apparatus according to claim 1 , wherein the logic circuit is further configured to generate a modified remaining capacity value based on the measured remaining capacity and the selected energy curve.
The invention relates to an apparatus for managing energy storage systems, particularly focusing on improving the accuracy of remaining capacity estimation in batteries or other energy storage devices. The core problem addressed is the inherent inaccuracy in determining the remaining usable energy of a battery due to factors like aging, temperature variations, and discharge rates, which can lead to unreliable capacity estimates. The apparatus includes a logic circuit that measures the remaining capacity of an energy storage device and selects an energy curve from a set of predefined curves. These curves represent different discharge profiles or degradation states of the battery. The logic circuit then generates a modified remaining capacity value by adjusting the measured capacity based on the selected energy curve. This modification accounts for deviations caused by real-world operating conditions, providing a more accurate estimate of the actual usable energy. The logic circuit may also include a processor and memory, where the memory stores the energy curves and any necessary algorithms for processing the measured capacity. The apparatus may further include a sensor interface to collect data from the battery, such as voltage, current, and temperature, which are used to refine the capacity estimation. By dynamically adjusting the remaining capacity value using the selected energy curve, the apparatus ensures more reliable energy management, particularly in applications where precise battery monitoring is critical, such as electric vehicles or renewable energy storage systems.
9. A method for monitoring a battery, comprising: measure a voltage of the battery; compute a remaining capacity of the battery based on the measured voltage; determine if the measured voltage is less than a predetermined threshold; select an energy curve from a plurality of energy curves based on the measured voltage of the battery when the measured voltage is determined to be less than the predetermined voltage; and determine a remaining energy value based on the selected energy curve and the computed remaining capacity.
This invention relates to battery monitoring systems, specifically for accurately estimating the remaining energy in a battery as its voltage decreases. The problem addressed is the inaccuracy of traditional battery monitoring methods that rely solely on voltage measurements, which become unreliable at low voltage levels. The invention improves upon these methods by dynamically adjusting the energy estimation process based on the battery's voltage state. The method involves measuring the battery's voltage and computing its remaining capacity from this measurement. If the voltage falls below a predetermined threshold, indicating a low-state condition, the system selects an appropriate energy curve from a predefined set of curves. These curves represent different voltage-to-energy relationships at various battery states. The selected curve is then used in conjunction with the computed remaining capacity to determine a more accurate remaining energy value. This approach compensates for the nonlinear behavior of batteries at low voltages, providing a more reliable energy estimate. The system ensures that the energy calculation adapts to the battery's condition, improving accuracy in real-world applications.
10. The method according to claim 9 , further comprising counting for a predetermined time period if the measured voltage is less than the predetermined threshold.
A method for monitoring electrical systems involves detecting voltage levels to identify potential faults or anomalies. The method measures the voltage of an electrical circuit and compares it to a predetermined threshold value. If the measured voltage falls below this threshold, the system initiates a counting process for a predetermined time period. This counting mechanism helps assess the duration or persistence of the low-voltage condition, which can indicate transient disturbances or sustained faults. The method may also include additional steps such as logging the event, triggering an alert, or initiating corrective actions based on the voltage measurements and the counting results. The counting period ensures that temporary voltage drops do not falsely trigger alarms, while prolonged low-voltage conditions are properly identified and addressed. This approach enhances the reliability of electrical system monitoring by distinguishing between transient and persistent voltage anomalies.
11. The method according to claim 10 , further comprising generating a modified remaining capacity based on the computed remaining capacity and the selected energy curve.
A method for managing energy storage systems addresses the challenge of accurately predicting and utilizing remaining battery capacity to optimize performance and longevity. The method involves computing a remaining capacity of an energy storage device, such as a battery, based on factors like state of charge, temperature, and degradation. To enhance accuracy, the method selects an energy curve from a set of predefined curves, where each curve represents different discharge or charge profiles. The selected curve is applied to adjust the computed remaining capacity, generating a modified remaining capacity that better reflects real-world operating conditions. This adjustment accounts for variations in energy delivery or absorption rates under different usage scenarios, improving energy management decisions. The method ensures that energy storage systems operate efficiently while minimizing degradation, extending their lifespan. By dynamically adapting the remaining capacity estimate using the selected energy curve, the system can optimize energy distribution, prevent over-discharge, and enhance overall reliability. This approach is particularly useful in applications requiring precise energy management, such as electric vehicles, renewable energy storage, and grid stabilization systems.
12. The method according to claim 9 , further comprising utilizing the remaining energy value estimate a lifespan of the battery.
A method for estimating the remaining energy of a battery and determining its lifespan involves monitoring the battery's operational parameters, such as voltage, current, and temperature, to assess its state of charge (SOC) and state of health (SOH). The method calculates the remaining energy by integrating the power output over time, adjusted for efficiency losses and environmental factors. By analyzing historical performance data and degradation trends, the method estimates the battery's remaining useful life. This includes predicting the point at which the battery can no longer meet performance thresholds, such as minimum voltage or capacity retention. The method may also incorporate machine learning models to refine predictions based on real-world usage patterns. The goal is to provide accurate estimates of both short-term energy availability and long-term durability, enabling better maintenance and replacement planning for battery systems. The approach is applicable to various battery chemistries and applications, including electric vehicles, grid storage, and portable electronics.
13. A system, comprising: a battery; a fuel gauge circuit connected to the battery and configured to: measure a voltage of the battery; compute a remaining capacity of the battery based on the measured voltage; store: a predetermined voltage threshold; and predetermined battery data comprising a plurality of energy curves; determine if the measured voltage of the battery is less than the predetermined voltage threshold; select one energy curve from the plurality of energy curves based on the measured voltage of the battery when the measured voltage is determined to be less than the predetermined voltage; and determine a remaining energy value based on the selected energy curve and the computed remaining capacity; and a load connected to the battery and the fuel gauge, wherein the fuel gauge controls a current to the load based on the remaining energy value.
A system for managing battery energy in electronic devices addresses the challenge of accurately estimating remaining battery life, particularly under varying load conditions. The system includes a battery, a fuel gauge circuit, and a load. The fuel gauge circuit measures the battery voltage and computes its remaining capacity. It stores a voltage threshold and a set of energy curves, which represent the battery's discharge characteristics under different conditions. When the measured voltage falls below the threshold, the circuit selects an appropriate energy curve based on the current voltage level. The remaining energy value is then calculated using this curve and the computed capacity. The fuel gauge adjusts the current supplied to the load according to this energy value, ensuring efficient power distribution. This approach improves accuracy in energy estimation, especially in low-voltage states, by dynamically adapting to the battery's discharge behavior. The system enhances battery longevity and performance by preventing over-discharge and optimizing power delivery.
14. The system according to claim 13 , wherein the fuel gauge circuit is further configured to count to a predetermined time.
A fuel gauge circuit is used in energy storage systems, such as batteries, to monitor and report the remaining charge. A common challenge in such systems is accurately determining the state of charge (SOC) while minimizing computational overhead and power consumption. Traditional methods often rely on complex algorithms or external processors, which can increase cost and complexity. This invention improves upon existing fuel gauge circuits by incorporating a timing mechanism that counts to a predetermined time. The circuit is designed to measure the charge level of a battery or energy storage device by tracking the time it takes to reach a specific charge threshold. By counting to a predetermined time, the circuit can efficiently estimate the remaining charge without requiring extensive computational resources. This approach simplifies the design, reduces power consumption, and improves reliability. The system may also include additional features, such as voltage monitoring, current sensing, and temperature compensation, to enhance accuracy. The timing-based measurement method allows for real-time SOC estimation while maintaining low power operation, making it suitable for portable and embedded applications.
15. The system according to claim 14 , wherein the fuel gauge circuit is further configured to re-start counting if the measured battery voltage is less than the predetermined threshold.
A system for monitoring battery fuel levels includes a fuel gauge circuit that measures battery voltage and determines fuel level based on the voltage. The system is designed to address inaccuracies in fuel level estimation caused by voltage fluctuations, particularly in low-voltage conditions. The fuel gauge circuit compares the measured battery voltage to a predetermined threshold. If the voltage falls below this threshold, the circuit re-initiates the counting process to ensure accurate fuel level tracking. This re-start mechanism prevents erroneous readings that could occur due to temporary voltage drops, improving the reliability of fuel level measurements. The system may also include additional components, such as a voltage measurement module and a processing unit, to support these functions. The re-start feature ensures that the fuel gauge adapts dynamically to voltage changes, maintaining precise fuel level data even under varying operating conditions. This solution is particularly useful in applications where battery performance is critical, such as electric vehicles or portable electronic devices.
16. The system according to claim 13 , wherein each energy curve from the plurality of energy curves comprises remaining energy values and corresponding remaining capacity values.
This invention relates to energy management systems for battery storage, particularly for optimizing energy distribution in electric vehicles or grid storage systems. The system addresses the challenge of accurately predicting battery performance over time, which is critical for efficient energy utilization and longevity. The core technology involves generating a plurality of energy curves, each representing the relationship between remaining energy and remaining capacity of a battery under different operating conditions. These curves are derived from real-time or historical battery data, accounting for factors such as charge/discharge cycles, temperature, and degradation. The system uses these curves to estimate the battery's state of charge and state of health, enabling precise energy management. By analyzing the energy curves, the system can optimize energy distribution, extend battery life, and improve overall system efficiency. The invention also includes methods for updating the energy curves dynamically as new data is collected, ensuring continuous adaptation to changing battery conditions. This approach enhances reliability and performance in applications where accurate energy prediction is essential.
17. The system according to claim 13 , wherein the fuel gauge circuit is further configured to generate a modified remaining capacity value based on the measured remaining capacity and the selected energy curve.
A system for fuel gauging in energy storage devices, such as batteries, addresses the challenge of accurately estimating remaining capacity under varying conditions. The system includes a fuel gauge circuit that measures the remaining capacity of the energy storage device and selects an energy curve from a set of predefined curves. The energy curve represents the relationship between the device's voltage and its remaining capacity under specific operating conditions. The fuel gauge circuit then generates a modified remaining capacity value by adjusting the measured remaining capacity based on the selected energy curve. This modification accounts for factors like temperature, load, or aging effects, improving the accuracy of the remaining capacity estimate. The system may also include a memory storing the energy curves and a processor to execute the fuel gauge circuit's functions. The energy curves can be derived from empirical data or predictive models, ensuring the system adapts to different usage scenarios. This approach enhances the reliability of battery management systems in applications where precise energy estimation is critical, such as electric vehicles or portable electronics.
18. The system according to claim 13 , wherein the fuel gauge circuit is further configured to estimate a lifespan of the battery based on the remaining energy value.
A battery monitoring system estimates the remaining energy of a battery and predicts its lifespan. The system includes a fuel gauge circuit that measures the battery's voltage, current, and temperature to calculate the remaining energy. This circuit also tracks the battery's charge and discharge cycles, adjusting the energy estimate based on environmental conditions and usage patterns. The system further analyzes historical data to predict the battery's remaining useful life, accounting for degradation factors like cycle count and temperature exposure. The lifespan estimation helps users anticipate replacement needs and optimize battery usage. The system may integrate with external devices to provide real-time monitoring and alerts. The fuel gauge circuit continuously updates the energy and lifespan estimates to ensure accuracy. This technology is useful in portable electronics, electric vehicles, and energy storage systems where battery performance and longevity are critical.
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October 31, 2019
March 15, 2022
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